Decoding the Principles of Emergence and Resiliency in Biological Collective Systems - A Multi-scale Approach
Abstract
Microbial communities are known to display complex, collective behaviors. However, the underlying principles as to how these behaviors arise despite uncertainty in molecular and cellular components of the system remains unclear. Consequently, we examine the robustness of collective behaviors in microbial communities, using pattern formation of wild coliform bacteria as a model system. Many coliform bacteria naturally form complex dynamic patterns that arise from the combination of chemotaxis, nutrient degradation, and the exchange of amino acids between cells. Using both quantitative experimental methods and several theoretical frameworks, we dissect bacterial pattern formation at multiple scales, from the molecules to individual cells to self-organizing populations. By comparing pattern formation from multiple wild isolates, we attempt to identify universal principles that govern robust, collective behaviors in biological systems. Towards this end, we adopt a multiscale approach combining experimental and theoretical approaches for the following research goals: (1) We develop a mathematical framework for characterizing and classifying the irregularity in microbial pattern formation and validate it against experimental measurements. (2) We determine the variability of protein copy numbers in living cells and develop a computational framework for measuring and predicting how noise in cellular components affects the overall system-level behavior. (3) In measurements of individual cells, we analyze behaviors such as chemotactic response, signaling potential, and swimming speed to predict how single-cell heterogeneity contributes to complex, collective behavior. (4) We develop a mathematical and experimental framework for identifying the single-cell functional states and quantify the cell-to-cell communication that lead to complex pattern formation. We define an information theoretic inspired framework for measuring how cell processing and cell-cell communication contribute to the degree of emergence, self-organization and robustness. (5) We propose a combined mathematical and experimental framework for investigating the robustness of pattern formation when two populations of pattern forming bacteria coexist in the same space. This project combines experimental tools including the tools of synthetic biology, fluorescence and brightfield microscopy at multiple length and time scales, and microfluidic functional assays of single-cell behavior with theoretical tools including agent-based models, non-equilibrium master equations, nonparametric statistics, systems of coupled partial differential equations, and novel analytical methods to predict and control the behavior of collective systems. In this performance period, we did not modify or made changes in the approach or methods.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 11, 2018
- Source ID
- W911NF1710076
Entities
People
- Paul Bogdan
Organizations
- Army Contracting Command
- Defense Advanced Research Projects Agency
- University of Southern California